Alzheimer’s disease is one of the most difficult brain disorders, and many fear they will suffer from it eventually. However, researchers now believe artificial intelligence can be used to predict Alzheimer’s, or at least detect the early signs of it.

A team from the University of California, Berkeley conducted a study to look at how artificial intelligence can predict Alzheimer’s. They trained the AI to detect early signs which may appear many years before the most dangerous symptoms begin.

It’s no secret that artificial intelligence is playing a bigger and bigger role in our daily lives. We use AI as assistants on our smartphones and to play games, but now more and more studies on the benefits of artificial intelligence are being conducted.

To predict Alzheimer’s, researchers trained the AI using a series of brain images from people who have been diagnosed with the disease. The brain images use “radioactive glucose compound,” also known as FDG, to help doctors detect areas of the brain with reduced metabolic activity.

“Differences in the pattern of glucose uptake in the brain are very subtle and diffuse,” study co-author Dr. Jae Ho Sohn told Medical Express. “People are good at finding specific biomarkers of disease, but metabolic changes represent a more global and subtle process.”

The team trained the artificial intelligence on over 2,100 FDG images to teach it to detect metabolism-related symptoms of Alzheimer’s disease with 100% accuracy. However, even though the team used that many FDG images to train their neural network, they tested it on only 40 separately-tested images which didn’t belong to the 2,100 images included in the training system.

The researchers said the study may not apply to all cases. It is a proof of concept more than anything else, and it can serve a great purpose in studies to come. The success of this study published by the Radiology Society of North America could inspire other experts to use AI to predict other dangerous diseases.

The UC Berkeley researchers are not the first to test AI in detecting Alzheimer’s disease. Another team of scientists from the Unlearn.AI startup designed software tools for clinical research, one of which is an AI system that predicts Alzheimer’s progression. However, the UC Berkeley team used an approach which focuses on a chemical marker that hasn’t been used before to train AI.

Author: Danica SimicDanica Simic has been writing ever since she was a child. Before she started writing for ValueWalk she was reviewing laptops, headphones and gaming equipment as well as writing articles about astronomy and game development. Danica is a student of applied and computational physics while also studying software and data engineering. Her hobbies include reading, swimming, drawing and gaming whenever she has free time. - Email her at dsimic@valuewalk.com